Improvements in digital recording and storage technology, together with the proliferation of digital and analog communication networks, have created a rapidly growing market for digital goods and services. The nature of digital goods is such that they can be reproduced at little cost. Thus, while it can be expensive to produce an original work, the marginal cost of producing additional copies is typically a negligible fraction of this initial cost. For example, commercial sound recordings, business reports, computer programs, and movies each typically cost a substantial sum to create; however, near-perfect digital copies can be produced easily and inexpensively using readily-available equipment. In the case of musical recordings, for example, digital formats such as MPEG-1 Audio Layer 3, or MP3, enable high-quality copies of an original recording to be stored and transmitted with relatively little consumption of disk space or network bandwidth.
While increasing attention has been devoted to the protection of digital and other electronic content from unauthorized copying, distribution, and use, relatively little attention has been paid to another fundamental problem facing the vendor of digital goods—namely, the problem of maximizing the value derived from the sale of those goods. Since digital goods can be produced at negligible marginal cost, they can be supplied in virtually unlimited quantities. Thus, the primary criteria for determining the optimal sale price for a digital work will typically be the utility value that consumers place on the work, which for practical purposes can be approximated by the amount consumers are willing to pay.
Accordingly, one measure of a digital work's value is the aggregate utility that consumers derive from the work. A vendor could recover this amount by charging each individual buyer the maximum amount that each is willing to pay. For example, if a first buyer valued a digitally-recorded movie at $5, a second buyer valued the movie at $8, and a third buyer valued the movie at $1, the vendor could maximize revenue by charging the first buyer $5, the second buyer $8, and the third buyer $1 for a copy of the movie. Of course, this amount will typically be unattainable in practice, as consumers are generally unwilling to pay a higher price than others for the same item simply because the item is more valuable to them. As a result, vendors typically estimate consumer utility via market analysis, and then use those estimates to set a fixed price designed to maximize revenue. In the example described above, for instance, the vendor could maximize revenue by setting the fixed price at $5, thus obtaining a revenue of $10 (i.e., $5 from the first and second buyers). Pay-per-view movies are an example of the use of fixed pricing for the sale of digital or electronic content.
Determining an optimal fixed price can be a difficult task, however, as it requires near-perfect knowledge of consumer utilities. If the price is set too high, an insufficient number of items may be sold; if the price is set too low, insufficient revenue may be collected per item. In the example presented above, if the vendor were to set the price at $6, he or she would only obtain $6 in revenue, as only the second buyer would be willing to purchase the movie. Similarly, if the price were set at $1, the vendor would obtain only $3. Moreover, since the utility value of an item may vary with time—for example, a consumer may not be willing to pay as much for a movie that was released a year ago as for a movie that was released yesterday—the vendor will need to make periodic attempts to re-adjust the fixed price.
In the context of limited-supply goods, auctions are sometimes used to determine the sale price. An advantage of an auction is that if it is properly designed, it will set the price for an item at or near the optimum fixed price. For example, in a conventional English auction bidders compete against each other to “win” an item at the bid price. Bidders continue raising the bid price until it exceeds the utility value of enough of the other bidders that the number of active bidders is equal to the number of items to be sold. Thus, the winning bidders effectively pay some increment above the utility value of the last bidder to withdraw from the auction.
Another auction technique was presented by Vickrey in his classic paper, Counterspeculation, Auctions and Competitive Sealed Tenders, Journal of Finance, (16) 8–37 (1961). In a typical Vickrey auction, bidders submit sealed bids to the auctioneer. If k items are being sold, the k highest bids win, but pay a price equal to the highest losing bid. That is, if the bids are ranked in ascending order from 1 to n, the k highest bids each pay the auctioneer an amount equal to the n−k highest bid. FIG. 1 illustrates a Vickrey auction in which ten bidders submit bids for k items. As shown in FIG. 1, if k=1 the highest bidder—in this case bidder 5, with a bid of $9—wins the auction and purchases the item for $8, which is the amount of the second highest bid (submitted by bidder 1). Similarly, if k=3 the three highest bidders (i.e., bidders 1, 4, and 5) win the auction, and each obtain one of the auctioned items for $6, which is the value of the fourth highest bid. A characteristic of the Vickrey auction is that each bidder has an incentive to bid his or her true utility value, since the price that each winning bid will pay is independent of the value of the winning bid itself. Accordingly, there is no reason for bidders to try to guess what other bidders are bidding and to bid incrementally above that value, as such a strategy runs the risk of missing an opportunity to buy the item at a price that is at or below the bidder's utility value, and does nothing to lower the price that the bidder will ultimately pay for the item if he or she wins. Auctions which encourage bidders to bid their true utility values are sometimes referred to as “stable” or “truthful” auctions.
Conventional auction techniques break down, however, if there is an unlimited supply of the goods being auctioned, as is the case with digital goods. (Note that “unlimited supply,” as used herein, refers generally to situations in which the seller has an amount of items that equals or exceeds demand, and/or situations in which the seller can reproduce items on demand at negligible marginal cost). For example, if the English auction described above were used to sell unlimited supply goods, bidders would have no incentive to raise the price in successive rounds, since all bids would be satisfied no matter what the bid value. Similarly, the Vickrey auction would be ineffective, as each bidder would pay an amount less than or equal to the lowest bid, which the bidders could set at an arbitrarily low level, knowing that it would nevertheless be satisfied. One way to avoid these problems is to artificially limit the supply of goods. However, it is apparent that this simply reintroduces the need for market analysis, since the problem of determining how to optimally limit supply so as to maximize revenue is typically no easier to solve than that of determining an optimal fixed price.
Accordingly, there is a need for systems and methods which enable the vendor of digital or other goods of unlimited supply to sell those goods without resort to costly and error-prone market analysis, yet which also enable the vendor to obtain a revenue stream that is of approximately the same order of magnitude as the revenue stream the vendor could receive if he or she had perfect information about the market for the goods.